The analysis of biological samples, food samples, potable water samples and pharmaceutical products for the presence of microorganisms is important and has important ramifications for safety, quality regulations and public health. For instance, recent outbreaks of food borne illness, implicating cheese and other dairy products contaminated with pathogenic bacteria, underscore the need for rapid methods for microbiological analysis.
In the traditional plate technique, a sample to be analyzed is cultured and the resulting colonies counted. The results of the test are obtained after a growth period ranging from a minimum of 1 day to as much as 7 to 8 days. In this technique, the growth period provides at one time, the distinction between viable and non-viable organisms, as well as the magnification of the signals from the viable organisms, to facilitate their detection at low concentration.
There is a crucial need for more rapid, more sensitive and more automated methods, for industrial as well as medical applications.
Rapid methods have been developed which are based on measuring the consequence of the metabolic activity of the microorganisms on a bulk property of the sample, such as impedance. All of these methods, called indirect methods, suffer from reduced sensitivity and still require culturing when the detection of low levels of contamination is required.
Other methods based on the direct counting of microorganisms have been developed recently. Among these, the direct epifluorescent filter techniques (DEFT) may be cited. In this technique the specimen to be analyzed is caused to pass through a filter which retains the microorganisms. The microorganisms are then made fluorescent and counted by visually analyzing the filter surface with an epifluorescence microscope. In this method, particles of interest are generally labelled with a fluorescent dye, such as acridine orange or other more specific dyes.
The visual analysis is tedious and complicated: first, because in the absence of a growth phase the organisms are quite small (requiring high power magnification for their detection), and second because the total area of the filter is so large that an impractical number of high power fields are required to cover the whole filter. Thus, typically only a small part of the filter is visually examined (less than 10%). This makes the technique inappropriate for sterility testing, where one single microorganism on the total filter has to be detected.
An additional problem with the DEFT technique is discrimination between the searched microorganisms and other particles, which are naturally fluorescent, that may have also been concentrated on the filter.
As a result of these problems, the repeatability and accuracy of the DEFT method are generally lower than that of the plate count methods. Other limitations of the DEFT include, low sensitivity, fading of intensity and operator fatigue, from prolonged use of the microscope.
The use of the epifluorescent microscope fitted with an image analyzer, in view to improve the DEFT technique has also been reported. However, although this is effective in eliminating subjectivity and operator fatigue, it is still limited by the fundamental problem that the organisms are small and the area to be covered is large.
In order to better understand this problem, it is useful to note that in electronic imaging systems the resultant image is made up of individual picture elements (pixels). In the current state of the art of electronic imaging, even the best video cameras can only form images of as many as 100,000 or 1 million pixels. However, the diameter of a single microorganism is typically around 1 .mu.m while the diameter of the filter is 25,000 .mu.m. Thus, if we consider one pixel to be the size of a microorganism, it would take 625 million pixels to cover the entire filter.
As a result either a single picture element (pixel) must be made much larger than the dimensions of a single microorganism or the analysis must include many sequential images. However, neither of these approaches is satisfactory. In the first case, the sensitivity of detection is lowered while, in the second case the time and complexity of analysis are limiting factors.
Another known means to improve the DEFT technique which may be considered is the use of a scanning confocal epifluorescence microscope. In this apparatus, a small laser spot is used to sequentially illuminate each element of the image field, while a detector positioned behind a small pinhole is also focused on the same element. The image is then formed from the detector signals in a manner similar to that described above for an electronic imaging system. In the optimum design of such an apparatus the dimensions of the illuminating spot is less than or equal to the dimensions of the smallest particle to be detected, and the dimensions of the pinhole is equal to or smaller than the dimensions of the illuminating spot.
The use of this known technology of scanning confocal microscopy is also not appropriate for this application, for at least the following reasons:
1) As stated above the ratio of the size of the filter to the area of the microorganism is greater than 100 million. Thus either a spot much larger than the organism must be used (with attending loss of sensitivity) or the scan time must be impractically long. PA1 2) In practical industrial samples, the membranes are both thick and not flat. Thus the microorganisms may be trapped at different levels in the pores of the filter membrane. As a result the region of the filter wherein the microorganisms of interest are trapped is not sufficiently well defined along the optical axis to permit the focusing optics to limit the depth of field which is a result of the insertion of a pinhole in front of the detector. PA1 3) An apparatus based on the above technology, performing high resolution scan of the entire filter would be very complex and expensive, and hence not practical for routine use. PA1 scanning a solid support on which a specimen potentially containing microorganisms has been deposited, the said sample having been subject to fluorescent staining, with an incident beam from a laser, forming a laser spot on the solid support, said laser spot being substantially greater than the microorganisms to be detected, said laser spot size being comprised between 4 and 14 .mu.m, wherein the distance between two scanning lines is such that each element of the support is scanned at least twice, by partial overlapping of adjacent scanning paths and is preferably less than half the dimension of said laser spot size; and simultaneously: PA1 detecting the resultant fluorescent light at least at one wavelength, by selecting only detected signals exceeding a given threshold (=samples), for instance a dynamic threshold, wherein a set of adjacent samples on a scan-line represents a feature; PA1 establishing a set of correlated-features by a line-to-line correlation of individual features, by comparing features on each pair of adjacent lines in time-synchrony, counting the number of lines over which said set of correlated-features occur, each set of correlated-features forming an event, and eliminating any single uncorrelated-features; PA1 correlation is considered as existing when one or more samples within the two features under comparison are detected in the same position on said pair of lines. The number of lines over which said set of correlated-features occur is counted, and thereafter used in size discrimination; PA1 comparing said correlated-features on each pair of adjacent lines in time synchrony, at least at two different wavelengths .lambda..sub.1 and .lambda..sub.2, for selecting the correlated-features having an emission intensity ratio at said two wavelengths lower than a predetermined number, being specified that if the emission ratio at said wavelengths generated by any correlated-samples is greater than a predefined value, the complete event is eliminated; PA1 making a size discrimination of retained events and selecting those having a size corresponding to a microorganism; PA1 determining if for retained events after size discrimination, the events energy profile in three dimensions is within predetermined Gaussian shape criteria and rejecting events not within said predetermined Gaussian shape criteria. Such analysis is for instance performed by a software curve-fitting algorithm. All events within the criteria are accepted as microorganism for the final count; those outside the criteria are classified as noise (dust or other contaminants on said solid support); PA1 counting said remaining events to determine and to count exclusively the microorganisms present on said solid support. PA1 determining the length of each event by counting the number of samples, by starting with the sample appearing first on the scanning direction on whatever feature of said event occurring the earliest, continue to include the sample appearing last in the scan direction on whatever feature ends last, said counting taking as one sample all the correlated samples on different scan lines, PA1 determining the width of said event by counting the number of adjacent lines covered by the same event and PA1 eliminating events for which the number of said counted samples is greater than a predetermined number A, and/or the number of said adjacent scan-lines is greater than a predetermined number B. PA1 collecting microorganisms from a specimen on a solid support, such as a filter membrane; PA1 labelling said microorganisms with a dye selected from the group constituted by vital dyes, viability markers, fluorescence substances carried by antibodies or nucleic probes, or generated by an enzyme linked probe system, capable, when excited, to produce an emission fluorescent at a wavelength .lambda..sub.1 ; PA1 scanning said solid support with an incident beam from a laser, forming a laser spot on said solid support, said laser spot being substantially greater than the microorganisms to be detected, said laser spot size being comprised between 4 and 14 .mu.m, wherein the distance between two scanning lines is such that each element of the support is scanned at least twice by partial overlapping of adjacent scanning paths and is preferably less than half the dimension of said laser spot size, and simultaneously: PA1 detecting the resultant fluorescent light at least at one wavelength, by selecting only detected signals exceeding a given threshold (=samples), wherein a set of adjacent samples on a scan-line represents a feature; PA1 establishing a set of correlated-features by a line-to-line correlation of individual features, by comparing features on each pair of adjacent lines in time synchrony, counting the number of lines over which said set of correlated-features occur, each set of correlated-features forming an event, and eliminating any single uncorrelated-features; PA1 correlation is considered as existing when one or more samples within the two features under comparison are detected in the same position on said pair of lines. The number of lines over which said set of correlating-features occur is counted, and thereafter used in size discrimination; PA1 comparing said correlated-features on each pair of adjacent lines in time synchrony, at least at two different wavelengths .lambda..sub.1 and .lambda..sub.2 for selecting the correlated-features having an emission intensity ratio at said two wavelengths lower than a predetermined number, being specified that if the emission ratio at said wavelengths generated by any correlated samples is greater than a predefined value, the complete event is eliminated; PA1 making a size discrimination of retained events and selecting those having a size corresponding to a microorganism; PA1 determining if for retained events after size discrimination, the events energy profile in three dimensions is within predetermined Gaussian shape criteria and rejecting events not within said predetermined Gaussian shape criteria. Such analysis is for instance performed by a software curve-fitting algorithm. All events within the criteria are accepted as microorganism for the final count; those outside the criteria are classified as noise (dust or other contaminants on said solid support); PA1 counting said remaining events to determine and to count exclusively the microorganisms present on said solid support. PA1 determining the length of each event by counting the number of samples, by starting with the sample appearing first on the scanning direction on whatever feature of said event occurring the earliest, continue to include the sample appearing last in the scan direction on whatever feature ends last, said counting taking as one sample all the correlated samples on different scan lines, PA1 determining the width of said event by counting the number of adjacent lines covered by the same event and PA1 eliminating events for which the number of said counted samples is greater than a predetermined number A, and/or the number of said adjacent scan-lines is greater than a predetermined number B. PA1 evaluation of the number of adjacent samples on a scan line (=feature), PA1 line to line correlation and PA1 number of correlated features in view to make a "size discrimination" as defined hereabove and to provide an accurate detection of microorganisms. PA1 the fluorescent response on any single scan line must be large enough to exceed a predetermined noise threshold; PA1 a feature must be detected with a predetermined degree of overlap on at least two consecutives line scans. PA1 dynamic thresholding of signal level: the data processing system continuously monitors background noise level, and adjusts the threshold level which features must exceed to be regarded as significant. This allows the system to tolerate variation in the behaviour of the membrane (solid support), both from membrane to membrane, and over the area of a single membrane; PA1 line-to-line correlation of signals: in order to be assigned as microorganism, features must be present on at least two scan lines; PA1 use of a green fluorescence spectrum shape for feature discrimination (red/green signal level). A feature detected in the green channel must have a corresponding red channel signal small or nil, as predicted from the shape of the green fluorescent marker emission spectrum. A higher level of red channel response will cause the feature to be rejected; PA1 signal discrimination: signals must be present for a predetermined number of scan points in order to be acceptable. Short signals are rejected as noise; PA1 correlated features comprising above a predetermined number of samples or above a predetermined number of lines (i.e., either along a given scan line, or across several line scans) are rejected. PA1 a laser light source for emitting an incident light beam, cooperating with means for focusing said laser beam into a laser spot, the dimension of which on a solid support is substantially greater than the microorganisms to be detected and counted, said laser spot size being comprised between 4 and 14 .mu.m; PA1 scanning means for directing the light from said light source onto said solid support to spotwise irradiate the microorganisms to produce fluorescence spots, wherein the distance between two scanning lines is such that each element of the support is scanned at least twice, by partial overlapping of adjacent scanning paths and is preferably less than the dimension of said laser spot size; PA1 means for detecting and photoelectrically converting said emitted fluorescence at least at two different wavelengths .lambda..sub.1 and .lambda..sub.2 ; PA1 means for discriminating and eliminating non-bacterial fluorescence including a digital signal processor and a plurality of optic paths for selecting at least two emission fluorescence wavelengths; PA1 signal processing means for establishing sets of correlated-features by a line-to-line correlation of individual features, by comparing features on each pair of adjacent lines in time synchrony, counting the number of lines over which said set of correlated-features occur, each set of correlated-features forming an event, and eliminating any single uncorrelated features, occurring only on one line; comparing said correlated-features on each pair of adjacent lines in time synchrony, at least at two different wavelengths .lambda..sub.1 and .lambda..sub.2, for selecting the correlated-features having an emission intensity ratio at said two wavelengths lower than a predetermined number, being specified that if the emission ratio at said wavelengths generated by any correlated features is greater than a predefined value, the complete event is eliminated; making a size discrimination of retained events and selecting the events having a size corresponding to a microorganism; determining if for retained events after size discrimination, the events energy profile in three dimensions is within predetermined Gaussian shape criteria and rejecting events not within said predetermined Gaussian shape criteria, and counting said remaining events to determine and to count exclusively the microorganisms present on said solid support.
Thus, in summary the known means of electronic image analysis either through the use of a video camera, a scanning apparatus, or combinations of these techniques are not suitable to the automation of the DEFT technique principally because of the large ratio between the size of the filter and the size of a single microorganism.